| Title |
Solving the Binary Puzzle with Genetic Algorithm |
|
Authors |
Balagbis, Rachel Anne B. ; Llantos, Orven E. |
|
Publication date |
2024/04/29 |
|
Journal |
Procedia Computer Science |
| Volume |
234 |
| Issue |
C |
| Pages |
954-961 |
| Publisher |
Elsevier B. V. |
| Abstract |
The increased internet usage after the pandemic led the UN Forum to improve cybersecurity measures, with zero-knowledge proofs (ZKP) being a viable solution for securing confidential information. ZKP protocols can be demonstrated through the binary puzzle, an NP-complete logic puzzle with four specific constraints. The key contribution of this paper is its successful implementation of the genetic algorithm as a new method to solve the binary puzzle. The optimized fitness function determined the solution at an average of 1.33-2.33 generations for populations ranging from 100 to 500. Its quadratic property calculated the solution faster than the ordinary linear fitness function. |
| Index terms / Keywords |
Zero-knowledge proof; Binary Puzzle; Genetic Algorithm; Artificial Intelligence; Fitness Function; NP-Complete |
| DOI |
|
| URL |
|
Mindanao State
University - Iligan Institute of Technology